# Monitoring & APM

Sedai correlates infra metrics with latency, errors, and traffic from your existing APM tools — no new agents, just smarter and safer optimization.

## Optimize Without Risking Performance

Your observability tools already capture how your services behave under load. Sedai considers that signal with every optimization decision, so infrastructure changes don't trade efficiency for reliability.

## Your Monitoring Stack Sees Everything. Optimization Doesn't.

APM and observability tools generate the right signal. It just never reaches the systems making resource decisions.

### Metrics live in silos.

CPU and memory sit in your cloud console. Latency and error rates live in Datadog or Dynatrace. Nothing connects them.

### Low utilization isn't the same as safe to reduce.

A service at 30% CPU might be absorbing bursts or sitting upstream of a latency-sensitive path.

### Alerts fire after the damage is done.

Tracing a regression back to the resource change that caused it means manual log digs and timeline comparisons.

## Key Capabilities

By connecting to your APM tools, Sedai moves beyond utilization metrics to understand how resource changes actually affect your applications.

### Correlate Infrastructure Metrics With Application Behavior

Sedai combines CPU and memory data with latency, error rates, and traffic signals, building a complete model of each workload before taking any action.

### Catch the Optimizations That Would Have Caused Problems

A service with low CPU utilization might still be latency-sensitive. Sedai identifies these cases and avoids changes that would reduce efficiency without improving safety.

### Connect Multiple Providers Into a Single Model

For instance, use CloudWatch for infrastructure metrics and Datadog for APM data simultaneously. Sedai correlates signals across all connected sources into one unified view of each workload.

"Sedai has helped us save millions of dollars by optimizing and managing our own back-end services. But most importantly, what Sedai has done very well is allow us to respond in real time when anomalies are detected."

— Suresh Sangiah, SVP of Engineering // Palo Alto Networks

## Works With Your Stack

### AppDynamics

### Chronosphere

### Datadog

### Dynatrace

### Elasticsearch

### Prometheus

### Cloud Monitoring

### Grafana

### Mimir

### Netdata

### New Relic

### Splunk

### VictoriaMetrics

### Wavefront

## The Sedai Difference

| Without Sedai | Sedai |
| --- | --- |
| Optimization decisions based on CPU and memory alone | Every decision accounts for latency, error rates, and traffic alongside infra metrics |
| APM tools and optimization tooling are disconnected workflows | Sedai connects directly to existing monitoring providers — no new agents required |
| Low utilization is treated as a safe signal to reduce resources | Sedai checks application behavior before acting — low CPU doesn't always mean safe to cut |
| A single monitoring source limits the accuracy of the model | Sedai connects multiple providers simultaneously for a unified workload view |
| SLO violations are discovered after the optimization is applied | Application performance signals are part of the safety check before every action |

## Resources

## Infrastructure Efficiency

That Doesn't Come at the Cost of Application Performance